1. Field
The present invention relates to a method and system for reverse osmosis predictive maintenance using normalization data.
2. Description of the Related Art
Conventional reverse osmosis units receive feed water and use filter banks to filter the feed water to remove deposits and generate permeate and concentrate. The permeate is the feed water with the deposits removed, while the concentrate is the excess waste. The percentage of permeate relative to the overall feed water is the percent recovery. However, performance of the reverse osmosis units is often dependent on the pressure of the feed water and the cleanliness of the filter banks. Thus, when the percent recovery is low, conventional methods and systems generally increase the pressure of the feed water, clean the filter banks, or replace the filter banks. However, increasing the feed water can damage the filter banks, necessitating their replacement, which can be costly over time. Furthermore, filter banks can also be cleaned only a limited amount of times before they must be replaced. Thus, if they are cleaned before they really need to be cleaned, they may need to be replaced quickly. Replacing the filter banks can also be expensive.
Thus, there is a need for a method and system for reverse osmosis predictive maintenance using normalization data.